Research On Temperature And Humidity Control Method Of Air Conditioning System

At present,the main problems faced by air conditioning system are how to improve the comfort of indoor environment and how to reduce the energy consumption of air conditioning.In order to improve the comfort of indoor environment,it is necessary to understand the influencing factors of thermal comfort index(PMV)and the control of the influencing factors,and one of the keys to reduce the energy consumption of air conditioning is to control the indoor environmental parameters more accurately and in time.In view of the problems existing in the above air conditioning system,the following work has been done in this paper:First,various factors that affect the comfort index are analyzed.Among the main factors of the analysis,the thermal comfort of the human body is the most important temperature and humidity in the hot and humid environment.Through the PSO-RBF neural network algorithm,the parameters of the prediction thermal comfort index model are studied and trained,and the network with better parameter value is obtained.Secondly,a simple temperature controller for air conditioning system is designed based on the combination of Smith predictive feedback control and traditional PID parameter tuning control.Then,the method of pole assignment and RBF neural network setting PID parameters is introduced.Inspired by the two-degree-of-freedom control,the feedforward controller is introduced,and the feedforward controller is combined with the Smith predictor-feedback controller.A two-degree-of-freedom composite controller for air-conditioning temperature with pole assignment setting PID parameters and a two-degree-of-freedom composite controller for setting PID parameters with RBF neural network are designed respectively.Finally,a PID iterative learning predictive control method based on two-dimensional frame theory is proposed for random interference in the actual operation of air-conditioning system.The method is used to simulate the humidity control of air-conditioning system.By comparing the tracking responses of different jamming signals,it is found that the iterative learning predictive control not only has better robustness to periodic interference,but also can keep better tracking performance under random interference conditions.Simulation results show that the proposed method is effective.The research results of this paper have a certain significance to change the simple PID control of the traditional air-conditioning system.By precisely controlling the temperatureand humidity of the air-conditioning system,the comfort of the human body in the air-conditioning environment can be greatly improved,and the environmental quality can also be improved.